IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v36y2011i2p854-863.html
   My bibliography  Save this article

Heat transfer using a correlation by neural network for natural convection from vertical helical coil in oil and glycerol/water solution

Author

Listed:
  • Colorado, D.
  • Ali, M.E.
  • García-Valladares, O.
  • Hernández, J.A.

Abstract

A physical–empirical model is designed to describe heat transfer of helical coil in oil and glycerol/water solution. It includes an artificial neural network (ANN) model working with equations of continuity, momentum and energy in each flow. The discretized equations are coupled using an implicit step by step method. The natural convection heat transfer correlation based on ANN is developed and evaluated. This ANN considers Prandtl number, Rayleigh number, helical diameter and coils turns number as input parameters; and Nusselt number as output parameter. The best ANN model was obtained with four neurons in the hidden layer with good agreement (R > 0.98). Helical coil uses hot water for the inlet flow; heat transfer by conduction in the internal tube wall is also considered. The simulated outlet temperature is carried out and compared with the experimental database in steady-state. The numerical results for the simulations of the heat flux, for these 91 tests in steady-state, have a R ≥ 0.98 with regard to experimental results. One important outcome is that this ANN correlation is proposed to predict natural convection heat transfer coefficient from helical coil for both fluids: oil and glycerol/water solution, thus saving time and improving general system performance.

Suggested Citation

  • Colorado, D. & Ali, M.E. & García-Valladares, O. & Hernández, J.A., 2011. "Heat transfer using a correlation by neural network for natural convection from vertical helical coil in oil and glycerol/water solution," Energy, Elsevier, vol. 36(2), pages 854-863.
  • Handle: RePEc:eee:energy:v:36:y:2011:i:2:p:854-863
    DOI: 10.1016/j.energy.2010.12.029
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054421000719X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2010.12.029?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Colorado-Garrido, D. & Santoyo-Castelazo, E. & Hernández, J.A. & García-Valladares, O. & Siqueiros, J. & Juarez-Romero, D., 2009. "Heat transfer of a helical double-pipe vertical evaporator: Theoretical analysis and experimental validation," Applied Energy, Elsevier, vol. 86(7-8), pages 1144-1153, July.
    2. Ko, T.H. & Ting, K., 2006. "Optimal Reynolds number for the fully developed laminar forced convection in a helical coiled tube," Energy, Elsevier, vol. 31(12), pages 2142-2152.
    3. Ekonomou, L., 2010. "Greek long-term energy consumption prediction using artificial neural networks," Energy, Elsevier, vol. 35(2), pages 512-517.
    4. Kalogirou, Soteris A. & Bojic, Milorad, 2000. "Artificial neural networks for the prediction of the energy consumption of a passive solar building," Energy, Elsevier, vol. 25(5), pages 479-491.
    5. De, S. & Kaiadi, M. & Fast, M. & Assadi, M., 2007. "Development of an artificial neural network model for the steam process of a coal biomass cofired combined heat and power (CHP) plant in Sweden," Energy, Elsevier, vol. 32(11), pages 2099-2109.
    6. Fast, M. & Palmé, T., 2010. "Application of artificial neural networks to the condition monitoring and diagnosis of a combined heat and power plant," Energy, Elsevier, vol. 35(2), pages 1114-1120.
    7. Wan, Kevin K.W. & Tang, H.L. & Yang, Liu & Lam, Joseph C., 2008. "An analysis of thermal and solar zone radiation models using an Angstrom–Prescott equation and artificial neural networks," Energy, Elsevier, vol. 33(7), pages 1115-1127.
    8. Satapathy, Ashok K., 2009. "Thermodynamic optimization of a coiled tube heat exchanger under constant wall heat flux condition," Energy, Elsevier, vol. 34(9), pages 1122-1126.
    9. Rusinowski, Henryk & Stanek, Wojciech, 2010. "Hybrid model of steam boiler," Energy, Elsevier, vol. 35(2), pages 1107-1113.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rashidi, M.M. & Galanis, N. & Nazari, F. & Basiri Parsa, A. & Shamekhi, L., 2011. "Parametric analysis and optimization of regenerative Clausius and organic Rankine cycles with two feedwater heaters using artificial bees colony and artificial neural network," Energy, Elsevier, vol. 36(9), pages 5728-5740.
    2. Huminic, Gabriela & Huminic, Angel, 2016. "Heat transfer and flow characteristics of conventional fluids and nanofluids in curved tubes: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1327-1347.
    3. Basak, Tanmay & Anandalakshmi, R. & Kumar, Pushpendra & Roy, S., 2012. "Entropy generation vs energy flow due to natural convection in a trapezoidal cavity with isothermal and non-isothermal hot bottom wall," Energy, Elsevier, vol. 37(1), pages 514-532.
    4. Li, Zhouhang & Zhai, Yuling & Bi, Dapeng & Li, Kongzhai & Wang, Hua & Lu, Junfu, 2017. "Orientation effect in helical coils with smooth and rib-roughened wall: Toward improved gas heaters for supercritical carbon dioxide Rankine cycles," Energy, Elsevier, vol. 140(P1), pages 530-545.
    5. Ebrahimzadeh, Edris & Wilding, Paul & Frankman, David & Fazlollahi, Farhad & Baxter, Larry L., 2016. "Theoretical and experimental analysis of dynamic heat exchanger: Retrofit configuration," Energy, Elsevier, vol. 96(C), pages 545-560.
    6. Movagharnejad, Kamyar & Mehdizadeh, Bahman & Banihashemi, Morteza & Kordkheili, Masoud Sheikhi, 2011. "Forecasting the differences between various commercial oil prices in the Persian Gulf region by neural network," Energy, Elsevier, vol. 36(7), pages 3979-3984.
    7. Liu, Penghua & Wang, Renting & Liu, Shaobei & Bao, Zewei, 2023. "Experimental study on the thermal-hydraulic performance of a tube-in-tube helical coil air–fuel heat exchanger for an aero-engine," Energy, Elsevier, vol. 267(C).
    8. Li, Zhouhang & Zhai, Yuling & Li, Kongzhai & Wang, Hua & Lu, Junfu, 2016. "A quantitative study on the interaction between curvature and buoyancy effects in helically coiled heat exchangers of supercritical CO2 Rankine cycles," Energy, Elsevier, vol. 116(P1), pages 661-676.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kljajić, Miroslav & Gvozdenac, Dušan & Vukmirović, Srdjan, 2012. "Use of Neural Networks for modeling and predicting boiler's operating performance," Energy, Elsevier, vol. 45(1), pages 304-311.
    2. Keçebaş, Ali & Alkan, Mehmet Ali & Yabanova, İsmail & Yumurtacı, Mehmet, 2013. "Energetic and economic evaluations of geothermal district heating systems by using ANN," Energy Policy, Elsevier, vol. 56(C), pages 558-567.
    3. Mikulandrić, Robert & Lončar, Dražen & Cvetinović, Dejan & Spiridon, Gabriel, 2013. "Improvement of existing coal fired thermal power plants performance by control systems modifications," Energy, Elsevier, vol. 57(C), pages 55-65.
    4. Ahadi, Mohammad & Abbassi, Abbas, 2015. "Entropy generation analysis of laminar forced convection through uniformly heated helical coils considering effects of high length and heat flux and temperature dependence of thermophysical properties," Energy, Elsevier, vol. 82(C), pages 322-332.
    5. Xu, Mingtian, 2012. "Variational principles in terms of entransy for heat transfer," Energy, Elsevier, vol. 44(1), pages 973-977.
    6. Amani, E. & Nobari, M.R.H., 2011. "A numerical investigation of entropy generation in the entrance region of curved pipes at constant wall temperature," Energy, Elsevier, vol. 36(8), pages 4909-4918.
    7. Movagharnejad, Kamyar & Mehdizadeh, Bahman & Banihashemi, Morteza & Kordkheili, Masoud Sheikhi, 2011. "Forecasting the differences between various commercial oil prices in the Persian Gulf region by neural network," Energy, Elsevier, vol. 36(7), pages 3979-3984.
    8. Almonacid, F. & Rus, C. & Pérez-Higueras, P. & Hontoria, L., 2011. "Calculation of the energy provided by a PV generator. Comparative study: Conventional methods vs. artificial neural networks," Energy, Elsevier, vol. 36(1), pages 375-384.
    9. Arslan, Oguz, 2011. "Power generation from medium temperature geothermal resources: ANN-based optimization of Kalina cycle system-34," Energy, Elsevier, vol. 36(5), pages 2528-2534.
    10. Rostek, Kornel & Morytko, Łukasz & Jankowska, Anna, 2015. "Early detection and prediction of leaks in fluidized-bed boilers using artificial neural networks," Energy, Elsevier, vol. 89(C), pages 914-923.
    11. Usón, Sergio & Valero, Antonio, 2011. "Thermoeconomic diagnosis for improving the operation of energy intensive systems: Comparison of methods," Applied Energy, Elsevier, vol. 88(3), pages 699-711, March.
    12. Hajmohammadi, M.R. & Eskandari, H. & Saffar-Avval, M. & Campo, A., 2013. "A new configuration of bend tubes for compound optimization of heat and fluid flow," Energy, Elsevier, vol. 62(C), pages 418-424.
    13. An, Ning & Zhao, Weigang & Wang, Jianzhou & Shang, Duo & Zhao, Erdong, 2013. "Using multi-output feedforward neural network with empirical mode decomposition based signal filtering for electricity demand forecasting," Energy, Elsevier, vol. 49(C), pages 279-288.
    14. Yeo, In-Ae & Yee, Jurng-Jae, 2014. "A proposal for a site location planning model of environmentally friendly urban energy supply plants using an environment and energy geographical information system (E-GIS) database (DB) and an artifi," Applied Energy, Elsevier, vol. 119(C), pages 99-117.
    15. Xu, Weijun & Gu, Ren & Liu, Youzhu & Dai, Yongwu, 2015. "Forecasting energy consumption using a new GM–ARMA model based on HP filter: The case of Guangdong Province of China," Economic Modelling, Elsevier, vol. 45(C), pages 127-135.
    16. Bahiraei, Farid & Saray, Rahim Khoshbakhti & Salehzadeh, Aidin, 2011. "Investigation of potential of improvement of helical coils based on avoidable and unavoidable exergy destruction concepts," Energy, Elsevier, vol. 36(5), pages 3113-3119.
    17. Li, Zhouhang & Zhai, Yuling & Bi, Dapeng & Li, Kongzhai & Wang, Hua & Lu, Junfu, 2017. "Orientation effect in helical coils with smooth and rib-roughened wall: Toward improved gas heaters for supercritical carbon dioxide Rankine cycles," Energy, Elsevier, vol. 140(P1), pages 530-545.
    18. Han, Yong & Wang, Xue-sheng & Zhang, Zhao & Zhang, Hao-nan, 2020. "Multi-objective optimization of geometric parameters for the helically coiled tube using Markowitz optimization theory," Energy, Elsevier, vol. 192(C).
    19. Jarungthammachote, Sompop, 2010. "Entropy generation analysis for fully developed laminar convection in hexagonal duct subjected to constant heat flux," Energy, Elsevier, vol. 35(12), pages 5374-5379.
    20. Li, Zhouhang & Zhai, Yuling & Li, Kongzhai & Wang, Hua & Lu, Junfu, 2016. "A quantitative study on the interaction between curvature and buoyancy effects in helically coiled heat exchangers of supercritical CO2 Rankine cycles," Energy, Elsevier, vol. 116(P1), pages 661-676.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:36:y:2011:i:2:p:854-863. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.